Recurrent Neural Networks for Network Intrusion Detection

Abstract

This Master thesis is the result of my research internship at IRIT. The goal was to study Deep Learning techniques such as Reccurent Neural Networks (RNN)for network intrusion detection. Using the widely used KD'99 network intrusion dataset, I implemented Long-Short Term Memory (LSTM) and Gated Recurrent Unit (GRU) models. I then compared my performance with other research results and tried to evaluate the model’s performance on other datasets.